Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

Abstract

Electric arc furnace applications in industry are related to position system of its pole, up and down of pole. The pole should be set the certain gap. These setting are needed to calibrate. It is done manually. In this research will proposed smart hydraulic to make this pole works as intelligent using proportional directional control valve. The output of this research will develop and improve the working of the electric arc furnace. This research requires study and design of the system to achieve the purpose and representation using Automation Studio software (AS), in addition to mathematically analyzed and where they were building a laboratory device similar to the design and conduct experiments to stud

Implementing smart community engagement should consider careful planning and collaboration with numerous stakeholders, including the community. The technology and program must be designed to frame its purpose and should link back to specific goals of implementing smart community engagement. Digital services do not guarantee a smart engagement between the community and the local government. This is the case for the Kubang Pasu local government where several online services have been provided in their attempt to implement the smart community concept. However, understanding on the preferences of features and requirements of existing web-based systems and the impact of these systems is lacking. Therefore, a perception study needs to be condu

Five rice (Oryza sativa L.) cultivars (N22, Amber, Moroberekan, Kinandang Patong, and Azucena) underwent path coefficient analysis across three plant spacings (15 cm × 15 cm, 20 cm × 20 cm, and 25 cm× 25 cm) in the summer of 2017 at the College of Agricultural Engineering Sciences, University of Baghdad, Al-Jadriya, Iraq. The experiment proceeded in a randomized complete block design (RCBD) with a split-plot arrangement and three replications. The main plots included three planting distances, and the subplot comprised five varieties. The traits studied were plant height, flag leaf area, number of tillers, panicle number, length and branches, grains per panicle, 1000-grain weight, and the percentage of unfilled grains. The results

This study is dedicated to solving multicollinearity problem for the general linear model by using Ridge regression method. The basic formulation of this method and suggested forms for Ridge parameter is applied to the Gross Domestic Product data in Iraq. This data has normal distribution. The best linear regression model is obtained after solving multicollinearity problem with the suggesting of 10 k value.

In the current work various types of epoxy composites were added to concrete to enhance its effectiveness as a gamma- ray shield. Four epoxy samples of (E/clay/B4C) S1, (E/Mag/B4C) S2, (EPIL) S3 and (Ep) S4 were used in a comparative study of gamma radiation attenuation properties of these shields that calculating using Mont Carlo code (MCNP-5). Adopting Win X-com software and Artificial Neural Network (ANN), µ/ρ revealed great compliance with MCNP-5. By applying (µ/ρ) output for gamma at different energies, HVL, TVL and MFP have been also estimated. ANN technique was simulated to estimate (µ/ρ) and dose rates. According to the results, µ/ρ of all epoxy samples scored higher than standard concrete. Both S2 and S3 samples having h

The presence of dyes in wastewater has become a major issue all over the world. The discharge of dyes in the environment is concerned for both toxicological and esthetical reasons. In this study, the removal of dyes from aqueous solution by electrocoagulation using aluminum electrodes as cathode and anode were investigated with the electrocoagulation cell of 1litter. The study included: the impact of various operating parameters on the dyes removal efficiency like pH, NaCl concentration, distance between electrodes, voltage, initial dyes concentration and type of electrodes. The dye (congo red) concentrations were (50, 100, 150, and 200 ppm), stirring speed was 120 rpm at room temperature. pH used was maintained constant

this work, a simple method was used to prepare the MnO2 nanoparticles. These nanoparticles then were characterized by several techniques, such as X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy (SEM) and atomic force microscope (AFM). The results showed that the diffraction peak of MnO2 nanoparticles was similar to that of standard data. The images of AFM and SEM indicated that the MnO2 nanorods were growing from the MnO2 nano spherical shape. PVA-pentaerythritol/MnO2 nanocomposite films were fabricated by evaporating casting method. The dielectric constant and loss tangent of P-Ery/MnO2 films were measured between 10 kHz and 1 MHz using LCR. As the content of MnO2 increased, the dielectric constant